scholarly journals The Potential Impacts of Electric Vehicles on Urban Air Quality in Shanghai City

2021 ◽  
Vol 13 (2) ◽  
pp. 496
Author(s):  
Xiaojian Hu ◽  
Nuo Chen ◽  
Nan Wu ◽  
Bicheng Yin
Keyword(s):  
Air Quality ◽  
Electric Vehicles ◽  
Public Transportation ◽  
Road Traffic ◽  
Urban Air Quality ◽  
Urban Air ◽  
Vehicular Emissions ◽  
Potential Reduction ◽  
Efficient Measure ◽  
Shanghai City

The Shanghai government has outlined plans for the new vehicles used for the public transportation, rental, sanitation, postal, and intra-city freight to be completely powered by electricity by 2020. This paper analyzed the characteristics of vehicle emissions in Shanghai in the past five years. The potential reduction in road traffic related emissions due to the promotion and application of electric vehicle in Shanghai was evaluated. The potential reduction was quantified by vehicular emissions. The vehicular emissions inventories are calculated by the COPERT IV model under the different scenarios, of which the results indicate that promoting electric vehicles is the efficient measure to control all road traffic related emissions and improve urban air quality. The results also provided basis and support for making policies to promote and manage electric vehicles.

Residents’ preferred measures and willingness-to-pay for improving urban air quality: A case study of Hanoi city, Vietnam

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Thanh Cong Nguyen ◽  
Hang Dieu Nguyen ◽  
Hoa Thu Le ◽  
Shinji Kaneko
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Willingness To Pay ◽  
Public Transportation ◽  
Online Survey ◽  
Urban Air Quality ◽  
Multivariate Probit ◽  
Urban Air ◽  
Content Type ◽  
Public Opinions

PurposeThis purpose of this paper is to understand residents’ choice of preferred measures and their willingness-to-pay (WTP) for the measures to improve the air quality of Hanoi city.Design/methodology/approachQuestionnaire surveys were conducted to collect the opinions of 212 household representatives living in Hanoi City. The survey tools were tested and adjusted through an online survey with 191 responses. Multivariate probit and linear regression models were used to identify determinants of respondents’ choices of measures and their WTP.FindingsRespondents expressed their strong preferences for three measures for air quality improvements, including: (1) increase of green spaces; (2) use of less polluting fuels; (3) expansion of public transportation. The mean WTP for the implementation of those measures was estimated at about 148,000–282,000 Vietnamese dong, equivalent to 0.09–0.16% of household income. The respondents’ choices appear to be consistent with their characteristics and needs, such as financial affordability, time on roads and their perceived impacts of air pollution. The WTP estimates increase with perception of air pollution impacts, time on roads, education and income; but are lower for older people.Originality/valueTo gain a better understanding of public opinions, we applied multivariate probit models to check whether respondents’ choices were consistent with their characteristics and perceptions. This appears to be the first attempt to test the validity of public opinions on choices of measures for improving urban air quality in Vietnam. Our WTP estimates also contribute to the database on the values of improved air quality in the developing world.

scholarly journals A comparison of two interaction matrix coding techniques used in a GIS-based tool for air quality assessment

2013 ◽  
Vol 8 (3) ◽  
pp. 306-314 ◽  
Keyword(s):  
Air Quality ◽  
Numerical Model ◽  
Road Traffic ◽  
Pollutant Dispersion ◽  
Urban Air Quality ◽  
Interaction Matrix ◽  
Urban Air ◽  
Weighting Factors ◽  
The Matrix ◽  
The Impact

The paper describes the development of a fast and easy-to-use qualitative tool for preliminary assessments of urban air quality related to road traffic. The tool is particularly aimed at the ability and budget of local government. It uses a novel interaction matrix-type methodology combined with mapping overlay, performed via a GIS. More specifically, the interaction matrix provides the weighting factors, which show the impact of each variable involved in a system on the target variable, air quality, as well as on the system as a whole. These weighting factors are used in the GIS to produce vulnerability maps. The maps visualise vulnerability to air pollution due to the combined effect of a number of interacting factors, and thus indicate areas susceptible to poor air quality. This results in a considerable reduction in computing time and complexity compared to the use of a sophisticated numerical model, as the user of the GIS tool only needs to perform mapping overlays in the GIS (using the previously derived weighting factors). The particular aim of this study was to compare two different methods for quantifying the interactions between variables in the matrix. The first method used constant coefficients, whose values are based on parametric studies performed using an advanced dispersion model or on good engineering judgement. The second method used a more sophisticated and versatile quantification of the interactions between variables, via analytical or semi-empirical relationships. In the latter method, the matrix was formulated computationally, so that the interaction weightings for different conditions can be obtained automatically. The technique was applied to the case study of an urban area with a high traffic throughput, in the UK. Two different interaction matrices were constructed for urban air quality linked to road traffic, based on the above methods. The GIS results based on both matrix methodologies were compared to the results of a more intensive dispersion numerical model in terms of pollutant dispersion patterns and hot spots. Both sets of results were shown to compare favourably with those of the numerical model. The results based on the more sophisticated matrix coding were found to be in closer agreement with those of the numerical model.

scholarly journals The impacts of road traffic on urban air quality in Jinan based GWR and remote sensing

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Qi Wang ◽  
Haixia Feng ◽  
Haiying Feng ◽  
Yue Yu ◽  
Jian Li ◽  
...  
Keyword(s):  
Air Quality ◽  
Road Network ◽  
Road Traffic ◽  
Intersection Number ◽  
Urban Air Quality ◽  
Network Density ◽  
Urban Air ◽  
Strong Positive Correlation ◽  
The Road ◽  
Bus Network

AbstractTraffic congestion and smog are hot topics in recent years. This study analyzes the impacts of road traffic characteristic parameters on urban air quality quantitatively based on aerosol optical thickness (AOD) and geographical weighted regression (GWR) models, including the road network density, road area occupancy, intersection number, and bus network density as main factors. There are some major research findings. Firstly, there exists a strong positive correlation between the peak congestion delay index (PCDI) and air quality, the correlation has R2 values of up to 0.4962 (R 0.70). Secondly, GWR refines the local spatial changes in the AOD and the road parameters, and the correlation R2 based GWR model all above 0.6. The correlation between AOD and the road area occupancy was the highest, and the correlations with the bus network density and the intersections number were higher than that with the road network density. Thus, bus route planning, bus emission reduction, road network planning, and signal timing (at intersections) have a greater impact on air quality than other policy, especially in areas with traffic jams. The results of this study could provide theoretical support for traffic planning and traffic control, and is promising in practice.

scholarly journals Analysis of the Impact of Road Traffic on the Urban Air Quality

2021 ◽  
Author(s):  
Qi Wang ◽  
Haixia Feng ◽  
Haiying Feng ◽  
Jian Li ◽  
Erwei Ning
Keyword(s):  
Air Quality ◽  
Road Network ◽  
Road Traffic ◽  
Urban Air Quality ◽  
Network Density ◽  
Urban Air ◽  
Traffic Planning ◽  
The Road ◽  
Bus Network ◽  
The Impact

Abstract With a focus on the hot topics of traffic congestion and smog (air quality), in this study, the impact of road traffic on urban air quality was the first quantitatively analyzed based on the aerosol optical thickness (AOD) and geographical weighted regression (GWR) models, including the road network density, road area occupancy, intersection number, and bus network density. The main research conclusions are as follows. There is a strong positive correlation between the peak congestion delay index (PCDI) and air quality. Based on the GWR model, AOD has high correlations with four road network traffic characteristic parameters, and these correlations are much higher than ordinary linear regression, that is, GWR refines the local spatial changes in the AOD and the road parameters. The correlation was mainly positive. The correlation between AOD and the road area occupancy was the highest, and the correlations between PM2.5 and the density of the bus network and the number of intersections were higher than those with the road network density. Thus, bus route planning, bus emission reduction, road network planning, and signal timing (intersection) have a greater impact on air quality, especially in areas with traffic jams. This study has a certain guiding significance for traffic planning and traffic control, and it provides support and a basis for traffic planning and control.

scholarly journals A very high-resolution assessment and modelling of urban air quality

2020 ◽  
Vol 20 (2) ◽  
pp. 625-647 ◽  
Author(s):  
Tobias Wolf ◽  
Lasse H. Pettersson ◽  
Igor Esau
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
High Resolution ◽  
Road Traffic ◽  
Urban Air Quality ◽  
City Centre ◽  
Urban Air ◽  
Wood Burning ◽  
The City ◽  
Very High

Abstract. Urban air quality is one of the most prominent environmental concerns for modern city residents and authorities. Accurate monitoring of air quality is difficult due to intrinsic urban landscape heterogeneity and superposition of multiple polluting sources. Existing approaches often do not provide the necessary spatial details and peak concentrations of pollutants, especially at larger distances from monitoring stations. A more advanced integrated approach is needed. This study presents a very high-resolution air quality assessment with the Parallelized Large-Eddy Simulation Model (PALM), capitalising on local measurements. This fully three-dimensional primitive-equation hydrodynamical model resolves both structural details of the complex urban surface and turbulent eddies larger than 10 m in size. We ran a set of 27 meteorological weather scenarios in order to assess the dispersion of pollutants in Bergen, a middle-sized Norwegian city embedded in a coastal valley. This set of scenarios represents typically observed weather conditions with high air pollution from nitrogen dioxide (NO2) and particulate matter (PM2.5). The modelling methodology helped to identify pathways and patterns of air pollution caused by the three main local air pollution sources in the city. These are road vehicle traffic, domestic house heating with wood-burning fireplaces and ships docked in the harbour area next to the city centre. The study produced vulnerability maps, highlighting the most impacted districts for each weather and emission scenario. Overall, the largest contribution to air pollution over inhabited areas in Bergen was caused by road traffic emissions for NO2 and wood-burning fireplaces for PM2.5 pollution. The effect of emission from ships in the port was mostly restricted to the areas close to the harbour and moderate in comparison. However, the results have contributed to implementation of measures to reduce emissions from ships in Bergen harbour, including provision of shore power.

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